In all experiments, we used multi-layer perceptrons (MLPs) with leaky ReLU activation functions [1]} as the discriminators \(D_k\)  and filters \(f_k\) .
The Appendix contains details on the exact hyperparameters (e.g., number of layers and sizes) used for all the different experiments, as well as details on the training procedures (e.g., number of epochs and data splits).
Code to reproduce our results is available at:
https://github.com/joeybose/Flexible-Fairness-Constraints.
